Your assignment is to do a detailed statistical analysis of the data to be able to decide later what would be appropriate control charts to monitor these variables.
The manager provides you data that the office has collected on these two variables:
Present a report to the manager with the results of the statistical analysis of the data and your conclusions on the variables that will be used to monitor the process performance.
| Time it takes since the patient checks-in until the patient checks-out | ||||
| Observation | Time (minutes) | |||
| 1 | 62.14 | |||
| 2 | 57.41 | |||
| 3 | 26.73 | |||
| 4 | 42.26 | |||
| 5 | 43.74 | |||
| 6 | 74.56 | |||
| 7 | 48.13 | |||
| 8 | 86.31 | |||
| 9 | 53.24 | |||
| 10 | 53.18 | |||
| 11 | 48.11 | |||
| 12 | 36.5 | |||
| 13 | 59.61 | |||
| 14 | 54.33 | |||
| 15 | 41.55 | |||
| 16 | 41.08 | |||
| 17 | 50.88 | |||
| 18 | 69.97 | |||
| 19 | 51.74 | |||
| 20 | 38.86 | |||
| 21 | 78.41 | |||
| 22 | 33.97 | |||
| 23 | 55.05 | |||
| 24 | 26.06 | |||
| 25 | 69.2 | |||
| 26 | 34.85 | |||
| 27 | 31.95 | |||
| 28 | 40.58 | |||
| 29 | 54.27 | |||
| 30 | 25.5 | |||
| 31 | 35.31 | |||
| 32 | 47.13 | |||
| 33 | 57.26 | |||
| 34 | 60.88 | |||
| 35 | 48.04 | |||
| 36 | 52.95 | |||
| 37 | 43.4 | |||
| 38 | 33.48 | |||
| 39 | 52.89 | |||
| 40 | 25.75 | |||
| 41 | 54.07 | |||
| 42 | 44.1 | |||
| 43 | 44.7 | |||
| 44 | 62.07 | |||
| 45 | 26.47 | |||
| 46 | 36.9 | |||
| 47 | 57.39 | |||
| 48 | 66.52 | |||
| 49 | 60.59 | |||
| 50 | 40.62 | |||
| 51 | 44.68 | |||
| 52 | 43.8 | |||
| 53 | 63.47 | |||
| 54 | 39.36 | |||
| 55 | 85.98 | |||
| 56 | 41.13 | |||
| 57 | 52.86 | |||
| 58 | 44.75 | |||
| 59 | 17.26 | |||
| 60 | 43.47 | |||
| 61 | 32.6 | |||
| 62 | 44.1 | |||
| 63 | 69.64 | |||
| 64 | 79 | |||
| 65 | 59.99 | |||
| 66 | 44.93 | |||
| 67 | 51.54 | |||
| 68 | 64.99 | |||
| 69 | 37.88 | |||
| 70 | 54.02 | |||
| 71 | 49.41 | |||
| 72 | 47.66 | |||
| 73 | 73.03 | |||
| 74 | 48.88 | |||
| 75 | 72.41 | |||
| 76 | 46.14 | |||
| 77 | 65.28 | |||
| 78 | 40.46 | |||
| 79 | 44.32 | |||
| 80 | 58.42 | |||
| 81 | 100.65 | |||
| 82 | 47.51 | |||
| 83 | 43.31 | |||
| 84 | 42.62 | |||
| 85 | 73.19 | |||
| 86 | 30.77 | |||
| 87 | 55.73 | |||
| 88 | 70.71 | |||
| 89 | 65.12 | |||
| 90 | 75.82 | |||
| 91 | 36.26 | |||
| 92 | 52.59 | |||
| 93 | 49.3 | |||
| 94 | 40.8 | |||
| 95 | 51.2 | |||
| 96 | 59.28 | |||
| 97 | 27.59 | |||
| 98 | 28.02 | |||
| 99 | 28.23 | |||
| 100 | 45.74 | |||
In: Statistics and Probability
Your assignment is to do a detailed statistical analysis of the data to be able to decide later what would be appropriate control charts to monitor these variables.
The manager provides you data that the office has collected on these two variables:
Present a report to the manager with the results of the statistical analysis of the data and your conclusions on the variables that will be used to monitor the process performance.
| Time it takes since the patient checks-in until the patient checks-out | ||||
| Observation | Time (minutes) | |||
| 1 | 62.14 | |||
| 2 | 57.41 | |||
| 3 | 26.73 | |||
| 4 | 42.26 | |||
| 5 | 43.74 | |||
| 6 | 74.56 | |||
| 7 | 48.13 | |||
| 8 | 86.31 | |||
| 9 | 53.24 | |||
| 10 | 53.18 | |||
| 11 | 48.11 | |||
| 12 | 36.5 | |||
| 13 | 59.61 | |||
| 14 | 54.33 | |||
| 15 | 41.55 | |||
| 16 | 41.08 | |||
| 17 | 50.88 | |||
| 18 | 69.97 | |||
| 19 | 51.74 | |||
| 20 | 38.86 | |||
| 21 | 78.41 | |||
| 22 | 33.97 | |||
| 23 | 55.05 | |||
| 24 | 26.06 | |||
| 25 | 69.2 | |||
| 26 | 34.85 | |||
| 27 | 31.95 | |||
| 28 | 40.58 | |||
| 29 | 54.27 | |||
| 30 | 25.5 | |||
| 31 | 35.31 | |||
| 32 | 47.13 | |||
| 33 | 57.26 | |||
| 34 | 60.88 | |||
| 35 | 48.04 | |||
| 36 | 52.95 | |||
| 37 | 43.4 | |||
| 38 | 33.48 | |||
| 39 | 52.89 | |||
| 40 | 25.75 | |||
| 41 | 54.07 | |||
| 42 | 44.1 | |||
| 43 | 44.7 | |||
| 44 | 62.07 | |||
| 45 | 26.47 | |||
| 46 | 36.9 | |||
| 47 | 57.39 | |||
| 48 | 66.52 | |||
| 49 | 60.59 | |||
| 50 | 40.62 | |||
| 51 | 44.68 | |||
| 52 | 43.8 | |||
| 53 | 63.47 | |||
| 54 | 39.36 | |||
| 55 | 85.98 | |||
| 56 | 41.13 | |||
| 57 | 52.86 | |||
| 58 | 44.75 | |||
| 59 | 17.26 | |||
| 60 | 43.47 | |||
| 61 | 32.6 | |||
| 62 | 44.1 | |||
| 63 | 69.64 | |||
| 64 | 79 | |||
| 65 | 59.99 | |||
| 66 | 44.93 | |||
| 67 | 51.54 | |||
| 68 | 64.99 | |||
| 69 | 37.88 | |||
| 70 | 54.02 | |||
| 71 | 49.41 | |||
| 72 | 47.66 | |||
| 73 | 73.03 | |||
| 74 | 48.88 | |||
| 75 | 72.41 | |||
| 76 | 46.14 | |||
| 77 | 65.28 | |||
| 78 | 40.46 | |||
| 79 | 44.32 | |||
| 80 | 58.42 | |||
| 81 | 100.65 | |||
| 82 | 47.51 | |||
| 83 | 43.31 | |||
| 84 | 42.62 | |||
| 85 | 73.19 | |||
| 86 | 30.77 | |||
| 87 | 55.73 | |||
| 88 | 70.71 | |||
| 89 | 65.12 | |||
| 90 | 75.82 | |||
| 91 | 36.26 | |||
| 92 | 52.59 | |||
| 93 | 49.3 | |||
| 94 | 40.8 | |||
| 95 | 51.2 | |||
| 96 | 59.28 | |||
| 97 | 27.59 | |||
| 98 | 28.02 | |||
| 99 | 28.23 | |||
| 100 | 45.74 | |||
In: Statistics and Probability
Your assignment is to do a detailed statistical analysis of the data to be able to decide later what would be appropriate control charts to monitor these variables.
The manager provides you data that the office has collected on these two variables:
Present a report to the manager with the results of the statistical analysis of the data and your conclusions on the variables that will be used to monitor the process performance.
| Time it takes since the patient checks-in until the patient checks-out | ||||
| Observation | Time (minutes) | |||
| 1 | 62.14 | |||
| 2 | 57.41 | |||
| 3 | 26.73 | |||
| 4 | 42.26 | |||
| 5 | 43.74 | |||
| 6 | 74.56 | |||
| 7 | 48.13 | |||
| 8 | 86.31 | |||
| 9 | 53.24 | |||
| 10 | 53.18 | |||
| 11 | 48.11 | |||
| 12 | 36.5 | |||
| 13 | 59.61 | |||
| 14 | 54.33 | |||
| 15 | 41.55 | |||
| 16 | 41.08 | |||
| 17 | 50.88 | |||
| 18 | 69.97 | |||
| 19 | 51.74 | |||
| 20 | 38.86 | |||
| 21 | 78.41 | |||
| 22 | 33.97 | |||
| 23 | 55.05 | |||
| 24 | 26.06 | |||
| 25 | 69.2 | |||
| 26 | 34.85 | |||
| 27 | 31.95 | |||
| 28 | 40.58 | |||
| 29 | 54.27 | |||
| 30 | 25.5 | |||
| 31 | 35.31 | |||
| 32 | 47.13 | |||
| 33 | 57.26 | |||
| 34 | 60.88 | |||
| 35 | 48.04 | |||
| 36 | 52.95 | |||
| 37 | 43.4 | |||
| 38 | 33.48 | |||
| 39 | 52.89 | |||
| 40 | 25.75 | |||
| 41 | 54.07 | |||
| 42 | 44.1 | |||
| 43 | 44.7 | |||
| 44 | 62.07 | |||
| 45 | 26.47 | |||
| 46 | 36.9 | |||
| 47 | 57.39 | |||
| 48 | 66.52 | |||
| 49 | 60.59 | |||
| 50 | 40.62 | |||
| 51 | 44.68 | |||
| 52 | 43.8 | |||
| 53 | 63.47 | |||
| 54 | 39.36 | |||
| 55 | 85.98 | |||
| 56 | 41.13 | |||
| 57 | 52.86 | |||
| 58 | 44.75 | |||
| 59 | 17.26 | |||
| 60 | 43.47 | |||
| 61 | 32.6 | |||
| 62 | 44.1 | |||
| 63 | 69.64 | |||
| 64 | 79 | |||
| 65 | 59.99 | |||
| 66 | 44.93 | |||
| 67 | 51.54 | |||
| 68 | 64.99 | |||
| 69 | 37.88 | |||
| 70 | 54.02 | |||
| 71 | 49.41 | |||
| 72 | 47.66 | |||
| 73 | 73.03 | |||
| 74 | 48.88 | |||
| 75 | 72.41 | |||
| 76 | 46.14 | |||
| 77 | 65.28 | |||
| 78 | 40.46 | |||
| 79 | 44.32 | |||
| 80 | 58.42 | |||
| 81 | 100.65 | |||
| 82 | 47.51 | |||
| 83 | 43.31 | |||
| 84 | 42.62 | |||
| 85 | 73.19 | |||
| 86 | 30.77 | |||
| 87 | 55.73 | |||
| 88 | 70.71 | |||
| 89 | 65.12 | |||
| 90 | 75.82 | |||
| 91 | 36.26 | |||
| 92 | 52.59 | |||
| 93 | 49.3 | |||
| 94 | 40.8 | |||
| 95 | 51.2 | |||
| 96 | 59.28 | |||
| 97 | 27.59 | |||
| 98 | 28.02 | |||
| 99 | 28.23 | |||
| 100 | 45.74 | |||
In: Statistics and Probability
| 1 | 49.67 |
| 2 | 30.14 |
| 3 | 18.83 |
| 4 | 22.67 |
| 5 | 50.09 |
| 6 | 89.11 |
| 7 | 79.95 |
| 8 | 49.19 |
| 9 | 70.29 |
| 10 | 57.92 |
| 11 | 53.37 |
| 12 | 22.44 |
| 13 | 29.91 |
| 14 | 72.20 |
| 15 | 42.63 |
| 16 | 83.28 |
| 17 | 18.02 |
| 18 | 76.63 |
| 19 | 89.25 |
| 20 | 19.48 |
| 21 | 12.33 |
| 22 | 72.71 |
| 23 | 46.25 |
| 24 | 31.58 |
| 25 | 36.24 |
| 26 | 32.19 |
| 27 | 65.90 |
| 28 | 40.32 |
| 29 | 64.30 |
| 30 | 59.03 |
| 31 | 44.74 |
| 32 | 86.43 |
| 33 | 12.66 |
| 34 | 28.66 |
| 35 | 67.27 |
| 36 | 56.42 |
| 37 | 87.76 |
| 38 | 36.30 |
| 39 | 86.69 |
| 40 | 23.34 |
| 41 | 96.76 |
| 42 | 85.48 |
| 43 | 87.58 |
| 44 | 47.26 |
| 45 | 68.13 |
| 46 | 73.56 |
| 47 | 90.61 |
| 48 | 58.80 |
| 49 | 99.11 |
| 50 | 13.87 |
| 51 | 54.05 |
| 52 | 57.91 |
| 53 | 39.68 |
| 54 | 72.75 |
| 55 | 29.89 |
| 56 | 11.72 |
| 57 | 79.42 |
| 58 | 35.75 |
| 59 | 35.44 |
| 60 | 47.51 |
| 61 | 84.39 |
| 62 | 49.04 |
| 63 | 62.55 |
| 64 | 41.23 |
| 65 | 66.10 |
| 66 | 91.06 |
| 67 | 47.32 |
| 68 | 67.71 |
| 69 | 73.65 |
| 70 | 94.65 |
| 71 | 73.05 |
| 72 | 46.01 |
| 73 | 23.01 |
| 74 | 31.65 |
| 75 | 57.84 |
| 76 | 72.30 |
| 77 | 54.58 |
| 78 | 30.61 |
| 79 | 96.07 |
| 80 | 52.86 |
| 81 | 31.36 |
| 82 | 42.77 |
| 83 | 10.14 |
| 84 | 32.26 |
| 85 | 45.10 |
| 86 | 33.71 |
| 87 | 54.59 |
| 88 | 74.71 |
| 89 | 47.22 |
| 90 | 25.29 |
| 91 | 59.88 |
| 92 | 62.41 |
| 93 | 94.63 |
| 94 | 38.03 |
| 95 | 57.27 |
| 96 | 10.73 |
| 97 | 57.72 |
| 98 | 24.58 |
| 99 | 79.24 |
| 100 | 18.83 |
Either copy & paste each answer from your data sheet, or round your answers to two decimal places where applicable.
Mean
Standard Error
Median
Mode (report #N/A if no mode)
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum/smallest
Maximum/Largest
Sum
Count
Did you notice the mistake in the video while using the data analysis tool? The data range to B1:B100 was selected instead of B1:B101 so there were only 99 values for the Count when the data analysis tool ran. Be sure not to make the same mistake.
In: Math
The data below are the heights of fathers and sons (inches). There are 8 rows in total.
Father Son
| 44 | 44 |
| 47 | 47 |
| 43 | 46 |
| 41 | 42 |
| 45 | 47 |
| 44 | 44 |
| 44 | 45 |
| 44 | 45 |
1. Which statistical test would you use to determine if there is a tendency for tall fathers to have tall sons and short fathers to have short sons? Test for the statistical significance.
2. Compute the regression equation for predicting sons' heights from fathers' heights.
3. Use the equation from #2 to predict the height of a son whose father is 46 inches tall.
4. Should you use the regression equation to predict the hight of a son whose father had a height of 25" when he was the same age as his son?
5. Which statistical test would you use to determine if generations get taller. The question is, are sons taller than their fathers were at the same age?
In: Math
We are interested in exploring the relationship between the weight of a vehicle and its fuel efficiency (gasoline mileage). The data in the table show the weights, in pounds, and fuel efficiency, measured in miles per gallon, for a sample of 12 vehicles.
| Weight | Fuel Efficiency |
|---|---|
| 2715 | 26 |
| 2520 | 24 |
| 2630 | 29 |
| 2790 | 38 |
| 3000 | 23 |
| 3410 | 25 |
| 3640 | 21 |
| 3700 | 27 |
| 3880 | 21 |
| 3900 | 19 |
| 4060 | 21 |
| 4710 | 15 |
Part (b)
r = -0.71 (correlation coefficient).Part (e)
What percent of the variation in fuel efficiency is explained by
the variation in the weight of the vehicles, using the regression
line? (Round your answer to the nearest whole number.)
%
Part (g)
For the vehicle that weighs 3000 pounds, find the residual
(y − ŷ).
(Round your answer to two decimal places.)
Does the value predicted by the line underestimate or overestimate
the observed data value?
underestimate or overestimate
Part (i)
The outlier is a hybrid car that runs on gasoline and electric technology, but all other vehicles in the sample have engines that use gasoline only. Explain why it would be appropriate to remove the outlier from the data in this situation.
The outlier lies directly on the line, so the error residual (y − ŷ) is zero. The outlier represents a different population of vehicles compared to the rest. The outlier is creating a curved least squares regression line. The outlier does not lie directly on the line, but it is close.
Remove the outlier from the sample data. Find the new correlation
coefficient and coefficient of determination. (Round your answers
to two decimal places.)
| correlation coefficient | |||
| coefficient of determination |
Find the new best fit line. (Round your answers to four decimal
places.)
ŷ = __ x + __
In: Statistics and Probability
Apple Corporation is structured into three divisions: Austin, Brown and Caden. Each division operates as a separate stand-alone business, and is designated as an investment centre. The company uses return on investment (ROI) to evaluate the performance of each division. For the purpose of calculating divisional ROI, invested capital is defined as total assets (net book value) less current liabilities, and divisional operating profits after tax are used. Each division is required to achieve an ROI of at least 9%. The following data relates to the financial performance of the divisions for the year of 2019: Austin Brown Caden Operating Profits $1,000 $900 $1,200 Total Assets (NBV) 18,000 4,000 36,000 Current Liabilities 8,000 1,000 11,000 ROI 10% 30% 4.8% Both Austin and Brown mainly operate education centers with focus on conducting computer and IT courses. Major assets of Austin Division include computer equipment, popular software and furniture and fixtures. All these assets have been used since the business was set up in 2016. No additional purchase of new assets was made. Although Brown operates in a similar business, it has different operational philosophy. Brown leases its computer equipment and software in order to have the most updated IT facilities for their customers. Therefore, the lease (rental) expenses account for a high percentage of its total operating expenses. Caden runs two restaurants which were newly set in 2019. The target customers are the highclass clusters. Therefore, high amount was spent on decent and splendid furniture and decoration. Based on the ROI calculation, the management would rank Brown as the top performer while Caden is required to put significant effort to improve its performance.
REQUIRED: ( At least 100 words)
Suggest TWO points in the case that needs to be taken into account when interpreting divisional performance by using ROI.
In: Accounting
Grant Corporation (C Corp) has two shareholders: Hugh (owns 50%) and Bullocks Corporation (50%). Grant Corporation makes $75,000 cash distribution to each shareholder on December 31, 2019. Hugh is an individual but Bullocks Corporation is a C Corporation. Hugh’s stock basis is $20,000 and Bullocks’ stock basis is $40,000. What are the tax consequences to Hugh and Bullocks on the distributions for each of the separate situations?
a. Current E&P is positive $40,000 and Accumulated E&P is negative $15,000.
b. Current E&P is negative $17,000 and Accumulated E&P is positive $27,000
In: Accounting
1. Compare and contrast four socioemotional theories of aging.
2. Describe some of the personality changes of late adulthood.
Define ageism, and provide two original examples of ageism.
Imagine that you are an older adult. Indicate and explain the policy issues of concern to you.
Indicate the role of attachment in later adulthood.
Explain what an elderly, ethnic woman can expect to experience during late adulthood.
If you were an older adult, what could you expect to happen to aspects of your social relations such as relationships with adult children and friendship?
8. Evaluate your own culture’s regard for the elderly in terms of the seven factors most likely to predict high status for the elderly.
Explain how the selective optimization with compensation model could help you age successfully.
In: Biology
street performer offers you a chance to play his game for the low price of $10.
His game involves you pushing two different buttons. One of the buttons, when pushed, has a 10% chance of winning you $40;
and the oth er button, when pushed, has a 20% chance of winning you $25. You are allowed two button presses( e ither pushing the same button twice or pushing each button once) in a single game.
Is it worth playing?
In: Math